Algorithmic Constitutionalism

• URL: http://arxiv.org/abs/2606.12437v1
• Date: Sat, 16 May 2026 13:16:32 GMT
• Title: Algorithmic Constitutionalism
• Abstract summary: We argue that the idea of ethical engineering is inadequate for the governance challenges posed by AI.<n>We develop an alternative framework, which we term "algorithmic constitutionalism"<n>The article elaborates the concept of algorithmic constitutionalism and demonstrates how it may be applied to Facebook's content moderation regime.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The increasing encroachment of artificial intelligence (AI) on social life raises significant risks for society, particularly within the infospheres created and controlled by companies such as Google, Facebook, Apple, and Amazon. This article examines these risks through an in-depth analysis of Facebook's content moderation regime, which is already partially governed by algorithms. We argue that the idea of ethical engineering, often proposed in the literature as a solution to the governance challenges posed by AI, is inadequate for several reasons. In response, we develop an alternative framework, which we term "algorithmic constitutionalism." Our approach rests on three pillars: (a) a layered architecture consisting of two levels of code: (i) an operative or object level and (ii) a meta level designed to protect the system's core principles from algorithmically initiated change; (b) algorithmic meta-reasoning, which enables the system to operate simultaneously at both levels so that it can monitor, verify, and potentially correct in real time operations at the object level that depart from principles protected at the meta-code level; and (c) correction through deliberation. The article elaborates the concept of algorithmic constitutionalism and demonstrates how it may be applied to Facebook's content moderation regime. As part of this analysis, we examine the tension between societal constitutionalism and algorithmic constitutionalism. Paradoxically, attempts to subject AI systems to external deliberative control may also enable AI agents to intervene in that process, potentially undermining its purpose. The article concludes by considering the implications of this argument for the European Digital Services Act, which entered into force in October 2022.

Related papers

• Understanding as an Explicit and Assessable Component of Frontier AI Safety Decisions [35.25345433558124]
  Decision makers need sufficient understanding to make good decisions about training or deploying frontier AI systems.<n>This paper builds on recent developments in safety cases using the Assurance 2.0 framework to operationalise the philosophical basis of understanding from Elgin and Arendt.
  arXiv  Detail & Related papers  (2026-08-20T09:12:36Z)
• Provably Secure Agent Guardrail [89.79561918065122]
  Existing defense architectures rely on empirical semantic guardrails and probabilistic large model adjudicators.<n>This paper proposes a new security paradigm for agents based on the fundamental limitations of logical reasoning.
  arXiv  Detail & Related papers  (2026-05-28T02:12:41Z)
• AI Deception: Risks, Dynamics, and Controls [153.71048309527225]
  This project provides a comprehensive and up-to-date overview of the AI deception field.<n>We identify a formal definition of AI deception, grounded in signaling theory from studies of animal deception.<n>We organize the landscape of AI deception research as a deception cycle, consisting of two key components: deception emergence and deception treatment.
  arXiv  Detail & Related papers  (2025-11-27T16:56:04Z)
• Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance [211.5823259429128]
  We propose a comprehensive framework integrating technical and societal dimensions, structured around three interconnected pillars: Intrinsic Security, Derivative Security, and Social Ethics.<n>We identify three core challenges: (1) the generalization gap, where defenses fail against evolving threats; (2) inadequate evaluation protocols that overlook real-world risks; and (3) fragmented regulations leading to inconsistent oversight.<n>Our framework offers actionable guidance for researchers, engineers, and policymakers to develop AI systems that are not only robust and secure but also ethically aligned and publicly trustworthy.
  arXiv  Detail & Related papers  (2025-08-12T09:42:56Z)
• Authoritarian Recursions: How Fiction, History, and AI Reinforce Control in Education, Warfare, and Discourse [0.0]
  Article theorizes how AI systems consolidate institutional control across education, warfare, and digital discourse.<n>Case studies are analyzed alongside cultural imaginaries such as Orwell's textitNineteen Eighty-Four, Skynet, and textitBlack Mirror, used as tools to surface ethical blind spots.
  arXiv  Detail & Related papers  (2025-04-12T01:01:26Z)
• Decoding the Black Box: Integrating Moral Imagination with Technical AI Governance [0.0]
  We develop a comprehensive framework designed to regulate AI technologies deployed in high-stakes domains such as defense, finance, healthcare, and education.<n>Our approach combines rigorous technical analysis, quantitative risk assessment, and normative evaluation to expose systemic vulnerabilities.
  arXiv  Detail & Related papers  (2025-03-09T03:11:32Z)
• It's complicated. The relationship of algorithmic fairness and non-discrimination regulations for high-risk systems in the EU AI Act [2.9914612342004503]
  The EU has recently passed the AI Act, which mandates specific rules for high-risk systems.<n>This paper aims to bridge the concepts of legal non-discrimination regulations and machine learning based algorithmic fairness concepts.
  arXiv  Detail & Related papers  (2025-01-22T15:38:09Z)
• Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks [55.2480439325792]
  This paper critically examines the European Union's Artificial Intelligence Act (EU AI Act) Uses insights from Alignment Theory (AT) research, which focuses on the potential pitfalls of technical alignment in Artificial Intelligence. As we apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
  arXiv  Detail & Related papers  (2024-10-10T17:38:38Z)
• Artificial intelligence in government: Concepts, standards, and a unified framework [0.0]
  Recent advances in artificial intelligence (AI) hold the promise of transforming government. It is critical that new AI systems behave in alignment with the normative expectations of society.
  arXiv  Detail & Related papers  (2022-10-31T10:57:20Z)
• Fairness in Agreement With European Values: An Interdisciplinary Perspective on AI Regulation [61.77881142275982]
  This interdisciplinary position paper considers various concerns surrounding fairness and discrimination in AI, and discusses how AI regulations address them. We first look at AI and fairness through the lenses of law, (AI) industry, sociotechnology, and (moral) philosophy, and present various perspectives. We identify and propose the roles AI Regulation should take to make the endeavor of the AI Act a success in terms of AI fairness concerns.
  arXiv  Detail & Related papers  (2022-06-08T12:32:08Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.